Pierre and Marie Curie University Can Tho University

139 Pages·2017·4.42 MB·English

Pierre and Marie Curie University
Can Tho University
Doctoral School EDITE de Paris
UMMISCO/IRD
INTEGRATING COGNITIVE MODELS OF HUMAN
DECISION-MAKING IN AGENT-BASED MODELS: AN
APPLICATION TO LAND USE PLANNING UNDER
CLIMATE CHANGE IN THE MEKONG RIVER DELTA
By Quang Chi TRUONG
Doctoral thesis of Informatics - Complex Systems Modeling
Under the direction of:
Mr. Alexis DROGOUL (Director)
Mr. Minh Quang VO (Co-director)

Presented and publicly defended on 07/12/2016 before the examining committee:
Mme. Amal EL FALLAH SEGHROUCHNI, Professor, UPMC (Jury president)
Mr. Jean-Christophe CASTELLA, Senior researcher, CIRAD (Reviewer)
Mr. Dominique LONGIN, Researcher, CNRS/IRIT (Reviewer)
Mr. Frédéric ROUSSEAUX, Assoc. Professor, University of La Rochelle (Examiner)
Mr. Alexis DROGOUL, Senior researcher, UMI 209 UMMISCO, IRD (Thesis director)
Mr. Minh Quang VO, Assoc. Professor, Can Tho University (Thesis co-director)
RÉSUMÉ
Titre de la thèse en français : Intégration de modèles cognitifs de la prise de décision
humaine dans les modèles à base d'agent : application à la planification de l’utilisation du sol
dans le Delta du Mékong en tenant compte du changement climatique.
Auteur : Quang Chi TRUONG
Directeur de thèse : M. Alexis DROGOUL
Co-directeur de thèse : M. Minh Quang VO
Encadrants : M. Benoit GAUDOU, M. Patrick TAILLANDIER et M. Trung Hieu
NGUYEN
Au Vietnam, l'aménagement du territoire agricole est une étape importante de la
planification gouvernementale. Les plans sont établis chaque dix ans sous l’égide de
l’Organisation des Nations unies pour l'alimentation et l'agriculture (FAO), et définissent en
même temps deux principaux objectifs : les types de culture qui doivent être développées en
priorité par les agriculteurs ; et les investissements en infrastructure à réaliser par les autorités.
Dans ce contexte, la précision de la planification est déterminante pour déterminer quelles
politiques publiques seront les plus appropriées. Cependant, concernant la dernière période de
planification (de 2000 à 2010) la comparaison entre ce que prévoyaient le plan en 2010 et les
cartes réelles d’occupation du sol la même année témoignent de profondes différences.
La raison principale de ce décalage entre planification et réalité n’est pas très claire,
mais nous faisons l’hypothèse dans ce travail qu’elle est liée à la complexité de la prise de
décision individuelle des agriculteurs. Les agriculteurs sont en effet ceux qui, en dernier
ressort, décident de l’usage final des parcelles agricoles. Et leurs comportements individuels
sont influencés par un ensemble de facteurs externes comme la planification, bien entendu,
mais aussi l’usage actuel des parcelles, certains facteurs socio-économiques et les
changements qui s’opèrent dans leur environnement immédiat (changement climatique,
montée et salinisation des eaux, etc.). En conséquence, ces comportements ne peuvent pas
être, encore, facilement représentés par les modèles prédictifs utilisés en planification (quand
ceux-ci les représentent). De nombreuses tentatives ont été faites, en particulier à l'aide
d'approches à base d'agents, pour modéliser plus finement les comportements des agriculteurs
et être ainsi capable de mieux planifier. Cependant, ces approches ont été limitées par des
choix de conception erronés ou par la puissance de calcul disponible. La représentation des
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processus de prise de décisions reste ainsi encore très simple dans la plupart des modèles de
planification agraire.
L'objectif initial de cette thèse est d’apporter une solution à ce problème en proposant,
premièrement, une approche cognitive basée sur le paradigme appelé Belief-Desire-Intention
(BDI) pour représenter les processus de prise de décision des acteurs humains, et
deuxièmement, une validation de cette approche dans le contexte d’un modèle complet de
changement d’usage des sols dans lequel la plupart des facteurs cités ci-dessus sont également
simulés. Le résultat de ce travail est une approche générique qui a été validée sur un modèle
intégrant le changement d’usage des sols d'une région située dans le Delta du Mékong au
Vietnam. Nos contributions principales sont les suivantes :
Intégration d’une architecture BDI au sein d'une plateforme de modélisation à base
d'agents (GAMA) ;
Conception d’un cadre générique baptisé « Multi-Agent Based Land-Use Change »
(MAB-LUC) permettant de modéliser et de simuler les changements d’usage des sols en
prenant en compte les décisions des agriculteurs ;
Proposition d’une solution permettant d’intégrer et d’évaluer les facteurs socio-
économiques et environnementaux dans le cadre de la planification agraire et d’intégrer
MAB-LUC dans le processus existant proposé par la FAO.
Ce travail, au-delà du cas d’étude concernant le Delta du Mékong, a enfin été conçu de
façon générique afin que la méthodologie utilisée puisse être généralisée à la modélisation de
systèmes socio-écologiques où les facteurs humains doivent être représentés avec précision.
Mots clés : Aménagement du territoire, Modélisation à base d’agent, BDI,
Modélisation avec agents cognitifs, Décision humaine, MAB-LUC, Modélisation des
changements d’usage des sols, Modélisation de systèmes socio-environnementaux.
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ABSTRACT
In Vietnam, land-use planning (LUP) is an important part of national public policies.
Decennial plans stipulate both how the land should be used by individuals, making the
implicit assumption that they will follow it, and which investments need to be undertaken by
authorities to support this use. A good accuracy of these plans is therefore essential to
establish correct public policies. However, as it has been the case for the period from 2000 to
2010, the actual land-use, which can be assessed by remote sensing technology or assessment
surveys, has been constantly at odds with the proposed plans, sometimes by an important
margin.
The main reason behind this discrepancy lies in the complexity of the decision-making
of farmers, who are the ones who ultimately decide how they will make use of their parcels.
The decision-making is an individual behavior, influenced by external factors like
institutional policies, land-cover and environmental changes, economic conditions or social
dynamics. Therefore, it cannot be easily represented in the predictive land-use models.
Several attempts which use agent-based modeling approaches (ABM) have been made in the
literature to simulate the decision-making of farmers. However, these approaches have been
systematically limited by design choice or by available computational capabilities. Therefore,
the represented decision-making processes are still very simple.
The initial goal of this thesis has been then to address this problem by proposing, on
one hand, a cognitive approach based on the Belief-Desire-Intention (BDI) paradigm to
represent the decision-making processes of human actors in agent-based models and, on the
second hand, a validation of this approach in a complete land-use change model in which
most of the factors cited above have also been simulated.
The outcome of this work is a generic approach, which has been validated in a
complex integrated land-use change model of a small region of the Vietnamese Mekong
Delta. Our main contributions have been:
The integration of the BDI architecture within an agent-based modeling platform
(GAMA);
The design of the Multi-Agent Based Land-Use Change (MAB-LUC) integrated
model that can take into account the farmers’ decision-making in the land-use change
processes;
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The proposal of a solution to assess the socio-economic and environmental factors in
land-use planning and to integrate the MAB-LUC model into the land-use planning process
of.
I conclude by showing that this work, designed in a generic fashion, can be reused and
generalized for the modeling of complex socio-ecological systems where individual human
factors need to be represented accurately.
Keywords: Agent-based Modeling, BDI, Cognitive modeling, Human Decision-
making, MAB-LUC, Land-use Change modeling, Land-use Planning, Socio-environmental
Modeling.
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ACKNOWLEDGEMENTS
I would like to express here my sincere thanks to those who gave me their help and
who have contributed to the realization of this thesis.
First and foremost, my sincere thanks go to my supervisor, Prof. Alexis Drogoul at the
IRD and the University Pierre and Marie Curie (UPMC), France, for the continuous support
of my Ph.D study and related researches. His supervision, advice, guidance and suggestion
helped me in all the time of research and writing of this thesis and research papers. Without
his motivation and persistent help this dissertation would not have been possible.
Beside my supervisor, I express my grateful thanks to the co-supervisors Assoc. Prof.
Benoit Gaudou at the IRIT, University of Toulouse Capitole 1 and Assoc. Prof. Patrick
Taillandier at the IDEES, University of Rouen for their advice, suggestion, guidance and
correction of the thesis and research papers as well as their help for the implementation of the
BDI architecture into the GAMA platform.
I would like to express my gratitude to the rest of my thesis committee: my co-
supervisors at the Can Tho University (CTU), Assoc. Prof. Vo Quang Minh and Assoc. Prof.
Nguyen Hieu Trung, for their helpful supervision and advice in my research in the specific
context in Vietnam and their encouragement in completing this study till the end.
The GAMA platform is an open source platform developed collaboratively by many
researchers. One part in Chapter 4 of my thesis is the result of this collaborative work. Thus, I
am extremely thankful to the GAMA developers, especially the BDI plug-in developers:
Assoc. Prof. Philippe Caillou from LRI, University Paris Sud; Mr. Mathieu Bourgais from
IDEES and Assoc. Prof. Carole Adam from the University of Grenoble for their works in
implementing the plug-in and for giving me a great chance to participate in this work.
This joint doctoral thesis between the UPMC and the CTU has received specific and
careful administrative help from both universities. First, I would like to thank Ms. Patricia
Zizzo for her help for administrative points at the UPMC. At the CTU side, I would like to
express my gratitude to the particular interest and support of the rector board of the CTU:
Assoc. Prof. Le Viet Dung, Prof. Nguyen Thanh Phuong, the vice rectors of the CTU. I would
like to thank also the Graduate School and the College of Environment and Natural Resources
of the CTU, especially Assoc. Prof. Mai Van Nam, Assoc. Prof. Nguyen Hieu Trung, Prof. Le
Quang Tri, Dr. Nguyen Xuan Hoang, Dr. Ngo Thuy Diem Trang, Ms. Nguyen Huu Giao Tien
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and Ms. Bui Thi Chuyen, without their strong support this complicated paperwork for the
joint doctoral thesis between the UPMC and the CTU could not be signed.
I would like to express my gratitude to the PDI-MSC Scholarship program from the
IRD and the UPMC for providing a postgraduate scholarship for me to conduct my research.
The chance to do my PhD research in the IRD and the UPMC has been one of the most
valuable opportunities in my career and I therefore feel grateful to all the professors of the
UMMISCO, the IRD, the UPMC and the doctoral school (EDITE), who provided me with
necessary related courses for my research. It is with immense gratitude that I acknowledge the
support and help of the program organizers, Prof. Jean-Daniel Zucker, Prof. Christophe
Cambier, Dr. Nicolas Marilleau and Ms. Kathy Baumont, during my visiting times in the IRD
– Bondy, France.
I would like also to thank the projects DREAM, PEERS-CLIMATIC and ARCHIVES,
funded by the IRD, where I benefited the budget for my four visiting times in UPMC, France
during my thesis.
I would thank the ICT Lab’s members of the University of Sciences and Technology
of Hanoi for their warm welcome during the period of writing this thesis. I would like to say a
really big thank you to Dr. Lai Hien Phuong who has taken a lot of times to review the
manuscript. I also thank my friends and colleagues Dr. Truong Xuan Viet, Dr. Truong Minh
Thai and specifically my PhD colleague Mr. Huynh Quang Nghi, for their suggestion for my
research and for their help with GAMA simulation platform.
The collected data of the thesis are supported by the provincial level project
coordinated by Prof. Vo Thi Guong, College of Agricultural and Applied Biology, the CTU;
the help from Ms. Tran Thi Hien, the DONRE of the Ben Tre province and the alternative
collection of data by my colleagues at CENRES, Dr. Vo Quoc Tuan, Ms. Tran Thi Ngoc
Trinh, Ms. Nguyen Thi Ha Mi and Mr. Cao Quoc Dat. I would like to thank them all for their
help.
Last but not the least, I would like to give my gratitude to my mother, my parents-in-
law and my brothers and sisters who always encourage me during a long period of this study.
On a personal note, I appreciate the sacrifices made by my wife, Hong Thao, to help me
through this journey. Without her unconditional love and patient support during this period,
this thesis would not be completed. And to my lovely daughter Thao Phuong, my son Quang
Phu, with all my heart.

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TABLE OF CONTENTS
RÉSUMÉ .................................................................................................................................... 1
ABSTRACT ............................................................................................................................... 3
ACKNOWLEDGEMENTS ....................................................................................................... 5
TABLE OF CONTENTS ........................................................................................................... 7
LIST OF FIGURES .................................................................................................................. 12
LIST OF TABLES ................................................................................................................... 15
CHAPTER 1 INTRODUCTION ............................................................................... 16
1.1 Agricultural Land-Use Planning in Vietnam ............................................................. 16
1.2 Anlyzis of the recent land-use plans issues in the Mekong Delta ............................. 18
1.3 Research questions .................................................................................................... 22
1.4 Objectives of the current research ............................................................................. 22
1.5 Contribution of the thesis .......................................................................................... 23
1.6 Structure of the thesis ................................................................................................ 24
CHAPTER 2 STATE OF THE ART ......................................................................... 26
2.1 Land-use and land-cover change models ................................................................... 26
2.1.1 Descriptive and explicative models .................................................................... 26
2.1.2 Bridging the gap: toward hybrid models ............................................................ 27
2.2 Decision-making of farmers concerning land-use change ........................................ 29
2.3 Brief introduction to decision-making in socio-ecological systems .......................... 31
2.3.1 Decision-making approaches for reactive agents ............................................... 31
2.3.2 Decision-making approaches for cognitive agents ............................................. 33
2.4 Agent architectures embedding decision-making processes ..................................... 35
2.4.1 Cognitive agent architectures ............................................................................. 36
2.4.2 BDI architectures ................................................................................................ 37
2.5 BDI architectures and platforms to simulate farmer behaviors ................................. 41
2.5.1 Agent architectures for representing farmer behaviors ...................................... 41
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2.5.2 BDI architecture in existing ABM platforms ..................................................... 42
2.6 Conclusion ................................................................................................................. 44
CHAPTER 3 THE BASIC MULTI-AGENT BASED MODEL OF LAND-USE
CHANGE (MAB-LUC) ........................................................................................................... 45
3.1 Basic integrated model for the land-use change ........................................................ 45
3.1.1 The conceptual model of the MAB-LUC ........................................................... 46
3.1.2 Modularity of the MAB-LUC ............................................................................ 47
3.2 Definition of the MAB-LUC ..................................................................................... 49
3.2.1 Economic Sub-model ......................................................................................... 50
3.2.2 Environmental sub-model .................................................................................. 53
3.2.3 Sub-model of farmers’ social influence ............................................................. 57
3.2.4 Farmer sub-model .............................................................................................. 58
3.2.5 Discussion about the farmer decision-making agent .......................................... 65
3.3 Conclusion ................................................................................................................. 66
CHAPTER 4 INTEGRATING A HUMAN DECISION-MAKING MODEL INTO
AN AGENT BASED MODEL ................................................................................................ 67
4.1 Principles of the human decision-making architecture .............................................. 68
4.2 Presentation of the GAMA BDI plug-in .................................................................... 70
4.2.1 Representation of knowledge of GAMA BDI agents ........................................ 70
4.2.1.1 Declaration of a BDI agent ................................................................................. 70
4.2.1.2 Predicates ........................................................................................................... 71
4.2.2 Behavior of agents .............................................................................................. 73
4.3 Integrating the BDI architecture into the sub-model of Farmers ............................... 75
4.3.1 Conceptual model of the farmers based on the BDI architecture ...................... 76
4.3.2 Desires base of farmers ...................................................................................... 77
4.3.3 Intentions base of farmers .................................................................................. 78
4.3.4 Set of plans defined for farmers ......................................................................... 79
4.4 Conclusion ................................................................................................................. 81
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CHAPTER 5 VALIDATION OF THE COGNITIVE AGENT IN LAND-USE
CHANGE MODELS ............................................................................................................. 82
5.1 Description of experiments ........................................................................................ 82
5.1.1 Experiment data .................................................................................................. 82
5.1.2 Indicators for simulation assessment .................................................................. 84
5.2 Calibration of the sub-model of the MAB-LUC ....................................................... 86
5.2.1 Calibration of the model of farmers using Markov-based decision approach ... 86
5.2.2 Calibration of the model of farmers using MCDM approach ............................ 87
5.2.3 Calibration of the model of Farmers using the BDI-based decision approach .. 87
5.3 Evaluation the MAB-LUC......................................................................................... 88
5.3.1 Experiment 1: The MAB-LUC using Markov-based decision approach ........... 88
5.3.2 Experiment 2: The MAB-LUC using the MCDM approach ............................. 91
5.3.3 Experiment 3: The MAB-LUC model using the BDI - based decision approach .
.................................................................................................................. 94
5.4 Assessment ................................................................................................................ 98
5.5 Conclusion ............................................................................................................... 100
CHAPTER 6 INTEGRATION OF THE LAND-USE CHANGE MODEL INTO
THE LAND-USE PLANNING PROCESS ........................................................................... 101
6.1 Integration of the MAB-LUC into the land-use planning process .......................... 101
6.2 Appraisal of socio-economic factors for land-use plans ......................................... 103
6.3 Appraisal of both socio-economic and environmental factors for land-use plans .. 106
6.4 Assessment of land-use plans under climate change ............................................... 108
6.5 Conclusion ............................................................................................................... 110
CHAPTER 7 CONCLUSION ................................................................................. 111
7.1 Contributions ........................................................................................................... 111
7.1.1 Contributions to agent-based modeling ............................................................ 111
7.1.2 Contributions for LUCC, LUP and assessment on impact of climate change . 111
7.2 Perspectives ............................................................................................................. 112
7.2.1 Improving the integrated model regarding the usage of uncertain data ........... 112
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